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Record W4390596819 · doi:10.1039/d3lc00904a

Centrifugal microfluidic system for colorimetric sample-to-answer detection of viral pathogens

2024· article· en· W4390596819 on OpenAlexafffund
Matthias Geißler, D. Brassard, Nadine Adam, Neda Nasheri, Ana Victoria C. Pilar, Kyle Tapp, Liviu Clime, Caroline Miville-Godin, Maxence Mounier, Christina Nassif, Ljuboje Lukic, Lidija Malic, Nathalie Corneau, Teodor Veres

Bibliographic record

VenueLab on a Chip · 2024
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsUniversity of OttawaHealth CanadaNational Research Council Canada
FundersNational Research Council CanadaHealth CanadaCanadian Food Inspection Agency
KeywordsMicrofluidicsMicrofluidic chipLab-on-a-chipChipSample (material)MultiplexingWorkflowChromatographyNanotechnologyComputer scienceMaterials scienceChemistryDatabase

Abstract

fetched live from OpenAlex

, seven) micropillar arrays in a narrow fluidic pathway can lead to variation (up to 50% or more) in the distribution of colorimetric signal deriving from the assay. Numerical modeling of flow behaviour was used to substantiate these findings. The technology-by virtue of automation-can provide a pathway toward rapid detection of viral pathogens, shortening response time in food safety surveillance, compliance, and enforcement as well as outbreak investigations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.214
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2024
Admission routes2
Has abstractyes

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